From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 46 more institutions on single bylines are not listed.

Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5Arts and Humanities · 2 works Computer Science · 2 works Artificial Intelligence · 2 works Language and Linguistics · 2 works Computer Vision and Pattern Recognition · 1 work

🧭 Topics 1Multilingual & cross-lingual NLP · 1 work

Works by year

2020s

20261 paper 20241 paper

Papers

The most cited first (OpenAlex and our library).

Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation Instructions (2024 · 99 citations)
Prior work on machine translation with LLMs mostly relies on few-shot in-context learning (ICL). For mid-sized models, weak ICL may hide how well they can actually translate. The authors test a different approach, multilingual Finetuning with Translation Instructions (mFTI). They cast each language pair as an…
Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text (2026 · 4 citations)
Training LLM agents for multi-turn tool use is limited by a shortage of realistic trajectories. Most existing synthesis methods start from a fixed API collection, so the data can only be as broad as that collection. The authors invert this approach. They argue that ordinary web text, such as how-to guides and…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation InstructionsTransactions of the Association for Computational Linguistics (TACL)Jiahuan Li, Hao Zhou, Shujian Huang, et al.2024 · 99 citations
DirectQE: Direct Pretraining for Machine Translation Quality Estimation ↗arXiv:2105.07149 · no summary yetQu Cui et al.2021 · 34 citations
Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from TextAnnual Meeting of the Association for Computational Linguistics (ACL)Zhihao Xu, Rumei Li, Jiahuan Li, et al.2026 · 4 citations
Formality is Favored: Unraveling the Learning Preferences of Large Language Models on Data with Conflicting Knowledge ↗Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · no summary yetJiahuan Li et al.2024 · 2 citations

Co-authors here

9 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
Transactions of the Association for Computational Linguistics (TACL): Transactions of the Association for Computational Linguistics (TACL) 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Cited by

Papers of our library cite their works 63 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated 2 November 2026

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🧑‍🔬 Jiahuan Li

🏛️ Affiliations

🧭 Fields, topics and concepts

📅 Works by year

2020s

📄 Papers

All works

🤝 Co-authors here

Venues

🔗 Cited by

Jiahuan Li

Affiliations

Fields, topics and concepts

Works by year

Papers

Co-authors here

Cited by